Knowledge-based algorithms to optimise e-learning outcome

Major providers of e-learning mostly design their products to aim at corporative organisations such as the universities. They are usually large systems with support only on very standard operations, lacking subsequently knowledge-based components to intelligently optimise the online delivery. In this work, we propose a number of concrete knowledge-based algorithms that would enable subject designers to effectively and efficiently select drill or assessment questions to target specific learning outcome, and at the same time automatically enrich the characterisation of such questions through their usage. The database structure and implementation issues are also addressed and analysed